In a study published in npj Digital Medicine, a team of researchers led by the University of Michigan developed a machine learning model that identified 17 environmental and social factors that can ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
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Financial word of the day: Heteroscedasticity — meaning, usage, and why it matters more than ever
Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...
New research shows mutual funds using machine learning strategies generate significant outperformance over traditional funds ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
YouTube offers free and flexible access to artificial intelligence educationStructured video content helps learners understand both basic and adv ...
Harvard University is providing seven free online courses in data science, each running for eight to nine weeks and requiring ...
Feasibility and Acceptability of Collecting Passive Smartphone Data for Potential Use in Digital Phenotyping Among Family Caregivers and Patients With Advanced Cancer This study applied three ...
ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
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